Skip to main content

TensorFlow Addons.

Project description

TensorFlow Addons is a repository of contributions that conform to well- established API patterns, but implement new functionality not available in core TensorFlow. TensorFlow natively supports a large number of operators, layers, metrics, losses, and optimizers. However, in a fast moving field like ML, there are many interesting new developments that cannot be integrated into core TensorFlow (because their broad applicability is not yet clear, or it is mostly used by a smaller subset of the community).

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

tfa_nightly-0.11.0.dev20200519011909-cp38-cp38-win_amd64.whl (894.6 kB view details)

Uploaded CPython 3.8Windows x86-64

tfa_nightly-0.11.0.dev20200519011909-cp38-cp38-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ x86-64

tfa_nightly-0.11.0.dev20200519011909-cp38-cp38-macosx_10_13_x86_64.whl (589.4 kB view details)

Uploaded CPython 3.8macOS 10.13+ x86-64

tfa_nightly-0.11.0.dev20200519011909-cp37-cp37m-win_amd64.whl (894.6 kB view details)

Uploaded CPython 3.7mWindows x86-64

tfa_nightly-0.11.0.dev20200519011909-cp37-cp37m-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.11.0.dev20200519011909-cp37-cp37m-macosx_10_13_x86_64.whl (589.4 kB view details)

Uploaded CPython 3.7mmacOS 10.13+ x86-64

tfa_nightly-0.11.0.dev20200519011909-cp36-cp36m-win_amd64.whl (894.6 kB view details)

Uploaded CPython 3.6mWindows x86-64

tfa_nightly-0.11.0.dev20200519011909-cp36-cp36m-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.11.0.dev20200519011909-cp36-cp36m-macosx_10_13_x86_64.whl (589.4 kB view details)

Uploaded CPython 3.6mmacOS 10.13+ x86-64

tfa_nightly-0.11.0.dev20200519011909-cp35-cp35m-win_amd64.whl (894.6 kB view details)

Uploaded CPython 3.5mWindows x86-64

tfa_nightly-0.11.0.dev20200519011909-cp35-cp35m-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.5mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.11.0.dev20200519011909-cp35-cp35m-macosx_10_13_x86_64.whl (589.4 kB view details)

Uploaded CPython 3.5mmacOS 10.13+ x86-64

File details

Details for the file tfa_nightly-0.11.0.dev20200519011909-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.11.0.dev20200519011909-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 894.6 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.3.1 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.7

File hashes

Hashes for tfa_nightly-0.11.0.dev20200519011909-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 e1a1237a14420a1f70c0a08e43024a778aac72056027f274a767eadd8d46eacf
MD5 68f9ce769ff5d893b7aee53a9fd5fb2a
BLAKE2b-256 d08e401d71f3ee00965d7b497c1e679c3f27c1b243e5855beaa35002aa052705

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200519011909-cp38-cp38-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200519011909-cp38-cp38-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 0632d9ac0a068578466b8d3b3f3fa9d41d213c9533a9a36eda47393f96d502f5
MD5 decf363d340dd4309597ef4edd80a09e
BLAKE2b-256 e9c68e50722f28668da18f78a52de74a1ad477942a8b6d519cc481b43bfcf820

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200519011909-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200519011909-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 1a627728cc33c454c95f7a461656e21e56d44306b9bea386a3f21a6ae097e745
MD5 1eacf0842bf14e5c0d024cfc0514151b
BLAKE2b-256 120e172701e8cf3743313d48feba3d98424ac3b4180a53263feef62d9cbdd54c

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200519011909-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.11.0.dev20200519011909-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 894.6 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.3.1 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.7

File hashes

Hashes for tfa_nightly-0.11.0.dev20200519011909-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 cde02048f226e3d5969c451a1a0cbab39d1cd9fb054934d3cca5244605fd0156
MD5 b7f68feee6c46915a69f4a29f2615284
BLAKE2b-256 e6dccc93acb9a6c20264287eca1639977fd61f571964ad3537d7cf06f4214be3

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200519011909-cp37-cp37m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200519011909-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 194dc5978be306d02efc35ff1c83b0ddec33957ed245a0b328a1f0e098c4a2b0
MD5 7b104d6d758997a9844f28a7d6e81e93
BLAKE2b-256 67b8cc9c7075cbae2d2002f47e9d9bec688a714c4c992210f23199d41cfa648d

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200519011909-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200519011909-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 20efe31c0c2b228a7ab936c4078492df12680ac298732a334c823a702cd1f673
MD5 4724dd553372773b801e3e7f37ff5368
BLAKE2b-256 f2c89ddf4d1ca7eb4bf7688ec9ef9f23b828f9e7f15b15e2951c8a53b09b4508

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200519011909-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.11.0.dev20200519011909-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 894.6 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.3.1 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.7

File hashes

Hashes for tfa_nightly-0.11.0.dev20200519011909-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 8d616d3836331968600ddcf0c3a67cc51acf4d610c85f9d8470bc24178136cc0
MD5 d20326545186fba294ae19f1b7e57eb5
BLAKE2b-256 a634c1dd6cfb44fe543fd32f78428f9c34180612b44fd3ae707fdc33dc6d9a1d

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200519011909-cp36-cp36m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200519011909-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 a4ea0fb9d11abd555572e92ea23f26bcb613d5c9aa8cf7a63959cde65d55df52
MD5 a58e22269e8e68ce19e96b1a077b6efb
BLAKE2b-256 44e7d29e7022eeff0f04c9121dd0f03009ca8137f209d71826bf2b22d612fddc

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200519011909-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200519011909-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 ca7618f8c7a883b2125a81c72d78147920b554c48cd61bb43c871b3e1a5f9abd
MD5 4cd20d559089d47300d0f0f7a2a0fc2b
BLAKE2b-256 ab7d73001019e4b9976a9abe6ed9313bebc624fa7113dce0f5fc4438af1316b2

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200519011909-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.11.0.dev20200519011909-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 894.6 kB
  • Tags: CPython 3.5m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.3.1 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.7

File hashes

Hashes for tfa_nightly-0.11.0.dev20200519011909-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 68ef4afeb582175bf7abcd5e360eda4a85215b0edd8c830f0bab2975dfd98f25
MD5 ceebebb0de15f5c6a761459d7d0f55fe
BLAKE2b-256 cd76100501c05dd75e340151e73976e102af7d88badffc40acbe1f553f349ffd

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200519011909-cp35-cp35m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200519011909-cp35-cp35m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 243e7977434eec7f82f0b4f4a8c5ca64ab138ed18e6b64745a33666ae790d58d
MD5 51b4f5492fb4b5efbbdbd2afa8035205
BLAKE2b-256 4de965a67dbac7837a5b96b631d493b90d5b3a2a5264893827189a9435802e5e

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200519011909-cp35-cp35m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200519011909-cp35-cp35m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 5c6a1eb9a2a87cbc0af9da7a4498c0d223e7764edf6fa7d6e30854750ed12c66
MD5 505d11bc48892d97df2f43bd17bb262c
BLAKE2b-256 ed3d031f79e829bf6be868f8dac077ce3b15fbbb6f70f4349531c631790d75fd

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page